Jobs at Micron Technology

Develop and deploy advanced semiconductor packaging technologies for high-performance memory products. Drive package integration, yield and quality improvements, cost reduction, process control, data analytics, and manufacturing readiness. Collaborate with process, product, assembly, test, reliability, and quality teams from technology development through high-volume production. Create process and model-of-record documentation and use Python, R, SQL, Visual Basic, and semiconductor control systems to analyze data and improve integration flows.

Owns development, qualification, and deployment of advanced semiconductor metrology applications for 3D NAND process development. The role focuses on FIB and complementary techniques such as AFM, SEM, and WLI, while evaluating next-generation systems, developing technology roadmaps, partnering with suppliers, and applying AI, machine learning, and data analytics to improve defect detection, yield, reliability, and manufacturing readiness.

Five-month internship analyzing semiconductor dry etch process and equipment data to identify variation, performance drift, productivity loss, and yield impacts. The intern will use statistical analysis, Python, SQL, JMP, Excel, dashboards, and AI-enabled methods to correlate manufacturing, metrology, and equipment data, then recommend process, hardware, recipe, or monitoring improvements.

Develop an AI-enabled dashboard for CMP equipment health and wafer breakage risk prediction. Analyze semiconductor manufacturing and equipment datasets, correlate maintenance and process indicators with breakage and yield excursions, build risk-scoring models, and create Power BI visualizations and automated engineering reports. The intern will collaborate with equipment engineers and gain experience in predictive analytics, reliability engineering, statistical analysis, and semiconductor manufacturing.

Performs electrical failure analysis and fault isolation on advanced semiconductor devices to identify root causes and improve product quality, reliability, and yield. Uses photon, thermal, and laser-stimulating tools, probe-test data, layouts, schematics, and physical failure analysis techniques. Develops fail-signature models, interprets findings, prepares technical reports, and collaborates with engineering teams. The role also applies AI-assisted tools responsibly to improve analysis efficiency and supports continuous improvement initiatives.

Lead internal cross-functional projects and programs from inception through delivery; plan and direct schedules and budgets; oversee project teams and external vendors; assign and monitor system analysis and program staff; integrate AI-assisted tools and promote AI literacy for improved efficiency.

Develop and optimize wafer-level semiconductor packaging processes, including wafer thinning and backside metal interconnects. Evaluate equipment and materials, establish process parameters, improve quality and yield through SPC, DOE, defect analysis, and advanced controls, and coordinate technology transfers from development through high-volume manufacturing. Collaborate across packaging, wafer fabrication, assembly, product engineering, and quality teams while documenting process and model records. Apply AI-enabled tools to improve analysis, efficiency, and operational outcomes.

Five-month internship focused on SSD depanel process characterization and optimization in semiconductor manufacturing. Responsibilities include executing statistical Design of Experiments, analyzing process and equipment data, identifying variation sources, establishing operating windows, developing visualizations, collaborating with engineering stakeholders, and evaluating AI-enabled tools for automated analysis, anomaly detection, reporting, and knowledge capture.

Senior Product Engineering role focused on functional and design validation of advanced NAND devices. Responsibilities include developing deterministic and pseudo-random Verilog test programs, automating validation with C, Python, and Perl, analyzing failures, identifying root causes, and driving cross-functional issue resolution. The role also applies AI/ML, data analytics, dashboards, and anomaly detection to improve test coverage, failure triage, debug productivity, and release readiness.

Coordinates process improvements for NAND Flash production, focusing on yield, quality, reliability, and output. Responsibilities include designing and analyzing experiments, investigating yield and quality issues, interpreting complex fab data, optimizing processes, communicating module issues, and leading cross-functional engineering initiatives. The role collaborates with production, process and equipment engineering, industrial engineering, technology development, and global partner teams while using AI-assisted tools to improve efficiency and operational outcomes.

Develop and optimize semiconductor metrology recipes for advanced packaging processes. Establish inspection methods, process monitoring strategies, control plans, SPC charts, and OCAPs. Analyze defect and yield data using statistical tools and dashboards, manage metrology equipment performance, and coordinate technology development with packaging, wafer fabrication, assembly, test, product engineering, and quality teams. The role requires semiconductor process or equipment engineering expertise, hands-on metrology experience, and strong programming and data analytics skills.

Supports the AI Process Intelligence team through Python automation prototypes, AI agent proofs of concept, predictive modeling, data pipelines, system connectors, controlled model testing, and technical documentation. Works under senior engineers and process architects in a structured, non-production environment while learning AI architecture, automation workflows, API integration, Agile development, DevOps, and knowledge integration.

Develop and execute functional and design validation flows for advanced NAND devices. Build automation infrastructure, deterministic tests, random sequence generators, and NAND interfaces using C-based programming, Python, and Perl. Apply AI/ML and data analytics to improve failure triage, root-cause analysis, validation coverage, and debugging. Perform electrical failure analysis across digital and analog circuitry, track validation metrics, and collaborate cross-functionally to resolve issues.

Develop AI-enabled automation workflows for NAND device characterization and engineering data analysis. Build data pipelines, machine learning models, anomaly detection tools, dashboards, AI assistants, and automated reporting solutions using large-scale semiconductor datasets. The role involves applying data science, generative AI, LLMs, and agentic AI to improve engineering productivity and decision-making while collaborating with cross-functional engineering teams.

Analyze semiconductor manufacturing and equipment datasets to identify Germhold patterns and root causes. Apply statistical analysis, machine learning, predictive analytics, and data visualization to develop improvement insights, dashboards, and reporting tools. Collaborate with process and equipment engineers to validate findings, evaluate AI-enabled solutions, and recommend ways to improve workstation efficiency, reduce Germholds, and enhance manufacturing capacity.

Lead data-driven process and test integration initiatives to improve high-value-bits yield (PG2+). Develop models and monitoring for tool performance, equipment prognostics, and test optimization. Prototype solutions with cross-functional teams, deploy best-known-methods to production, and integrate AI-assisted tools to drive continuous improvement and operational excellence.

The role involves developing reliability test flows, managing qualification plans, driving innovation, mentoring team members, and ensuring project execution through cross-functional collaboration.

Perform independent lab analyses to support IC package development, including materials characterization and physical failure analysis using SAM, X-ray, SEM, FIB and cross-sectioning. Maintain lab tools, supplies, calibration, and 6S cleanliness. Integrate AI-assisted tools to improve processes and collaborate with team, working overtime when required.

Designs and supports chemical and gas delivery systems for semiconductor facilities. Responsibilities include capacity and infrastructure planning, code compliance, equipment startup and integration, critical component specification, contractor and OEM coordination, troubleshooting, SOP and risk assessment improvements, safety compliance, database maintenance, and implementation of AI-augmented or automated process improvements. The role also supports quality management system effectiveness and continuous improvement.

Leads global manufacturing equipment and capacity modeling, optimizing tool utilization, throughput, capital deployment, process flexibility, and equipment repurposing. Analyzes the financial and operational impacts of manufacturing changes, develops benchmarks and reports, and coordinates implementation across manufacturing, engineering, finance, procurement, supply chain, production, and planning teams. The role also explores AI-enabled tools to improve planning, reporting, and optimization.